U.S. patent application number 12/970732 was filed with the patent office on 2012-06-21 for on-line social search.
This patent application is currently assigned to Yahoo! Inc.. Invention is credited to Farzin Maghoul, Shiv Ramamurthi.
Application Number | 20120158715 12/970732 |
Document ID | / |
Family ID | 46235757 |
Filed Date | 2012-06-21 |
United States Patent
Application |
20120158715 |
Kind Code |
A1 |
Maghoul; Farzin ; et
al. |
June 21, 2012 |
ON-LINE SOCIAL SEARCH
Abstract
Example methods, apparatuses, or articles of manufacture are
disclosed that may be implemented using one or more computing
devices to facilitate or otherwise support one or more processes or
operations in connection with performing information searches, such
as, for example, domain-specific on-line searches using social
survey-type queries.
Inventors: |
Maghoul; Farzin; (Hayward,
CA) ; Ramamurthi; Shiv; (San Francisco, CA) |
Assignee: |
Yahoo! Inc.
Sunnyvale
CA
|
Family ID: |
46235757 |
Appl. No.: |
12/970732 |
Filed: |
December 16, 2010 |
Current U.S.
Class: |
707/728 ;
707/E17.014 |
Current CPC
Class: |
G06F 16/951 20190101;
G06Q 10/10 20130101; G06F 16/9535 20190101 |
Class at
Publication: |
707/728 ;
707/E17.014 |
International
Class: |
G06F 17/30 20060101
G06F017/30 |
Claims
1. A method comprising: electronically processing a social survey
query of a user applied to one or more on-line social networks of
said user; wherein results received in response to one or more
digital signals representing said social survey query are ranked
based, at least in part, on social relevance to said user.
2. The method of claim 1, wherein said electronically processing
said social survey query further comprises: electronically
processing said social survey query using at least one
language-modeling technique.
3. The method of claim 1, wherein said electronically processing
said social survey query further comprises: electronically
processing said social survey query using at least one pattern
matching technique.
4. The method of claim 1, wherein said electronically processing
said social survey query further comprises: electronically
obtaining socially relevant on-line information in connection with
one or more members of one or more on-line social networks of said
user.
5. The method of claim 4, wherein said socially relevant on-line
information comprises socially relevant public on-line
information.
6. The method of claim 4, wherein said socially relevant on-line
information comprises socially relevant private on-line
information.
7. The method of claim 1, wherein said one or more on-line social
networks of said user comprises one or more on-line domain-specific
social networks of said user.
8. The method of claim 1, wherein said one or more on-line social
networks of said user comprises one or more on-line domain-specific
social sub-graphs of said user.
9. The method of claim 1, wherein said results received in response
to one or more digital signals representing said social survey
query are ranked based, at least in part, on chronological ordering
of said results.
10. The method of claim 1, wherein said social relevance to said
user comprises at least one of the following: explicit social
relevance to said user; implicit social relevance to said user; or
any combination thereof.
11. An article comprising: a storage medium having instructions
stored thereon executable by a special purpose computing platform
to: electronically process a social survey query of a user applied
to one or more on-line social networks of said user; wherein
results received in response to one or more digital signals
representing said social survey query are ranked based, at least in
part, on social relevance to said user.
12. The article of claim 11, wherein said storage medium having
instructions to electronically process said social query further
includes instructions to: electronically process said social survey
query using at least one of the following: a language-modeling
technique; a pattern matching technique; or any combination
thereof.
13. The article of claim 11, wherein said storage medium having
instructions to electronically process said social query further
includes instructions to: electronically obtain socially relevant
on-line information in connection with one or more members of one
or more on-line social networks of said user.
14. The article of claim 11, wherein said one or more on-line
social networks of said user comprises at least one of the
following: an on-line domain-specific social network of said user;
an on-line domain-specific social sub-graph of said user; or any
combination thereof.
15. The article of claim 11, wherein said social relevance to said
user comprises at least one of the following: explicit social
relevance to said user; implicit social relevance to said user; or
any combination thereof.
16. An apparatus comprising: a computing platform enabled to:
electronically communicate a social survey query of a user to be
processed and then applied to one or more on-line social networks
of said user; wherein results received in response to one or more
digital signals representing said social survey query are ranked
based, at least in part, on social relevance to said user.
17. The apparatus of claim 16, wherein said computing platform is
further enabled to: electronically display a listing of said
results to represent socially relevant on-line information in
connection with one or more members of one or more on-line social
networks of said user.
18. The apparatus of claim 16, wherein said one or more on-line
social networks of said user comprises at least one of the
following: an on-line domain-specific social network of said user;
an on-line domain-specific social sub-graph of said user; or any
combination thereof.
19. The apparatus of claim 16, wherein said social relevance to
said user comprises at least one of the following: explicit social
relevance to said user; implicit social relevance to said user; or
any combination thereof.
20. The apparatus of claim 16, wherein said results received in
response to one or more digital signals representing said social
survey query are ranked based, at least in part, on chronological
ordering of said results.
21. A method comprising: combining and organizing socially relevant
content to a particular user, said socially relevant content
including responses from a social network or social sub-network of
said particular user; and electronically directing said particular
user to a search engine capable of searching said socially relevant
content.
22. The method of claim 21, wherein said search engine capable of
searching said socially relevant content is capable of searching
said content by performing, at least in part, a faceted social
search.
23. The method of claim 21, wherein said responses from said social
network or social sub-network of said particular user comprises at
least one of the following: responses from a private social network
or social sub-network of said particular user; responses from a
public social network or social sub-network of said particular
user; or any combination thereof.
24. The method of claim 21, wherein said socially relevant content
is organized based, at least in part, on at least one of the
following: social relevance to said particular user; chronological
ordering of said socially relevant content; or any combination
thereof.
25. The method of claim 24, wherein said social relevance to said
particular user comprises at least one of the following: explicit
social relevance to said particular user; implicit social relevance
to said particular user; or any combination thereof.
Description
BACKGROUND
[0001] 1. Field
[0002] The present disclosure relates generally to search engine
information management and, more particularly, to on-line social
searching or surveying techniques.
[0003] 2. Information
[0004] The Internet is widespread. The World Wide Web or simply the
Web, provided by the Internet, continues to grow rapidly, at least
in part, from new information seemingly being added daily. A wide
variety of online information, such as, for example, web pages,
text documents, images, audio files, video files, or the like, is
continually being identified, located, retrieved, accumulated,
stored, or communicated. With a large amount of information being
available over the Internet, a number of tools or services may
often be provided to users so as to allow for copious amounts of
information to be searched through in an efficient or effective
manner. For example, service providers may allow users to search
the Web or other like networks using search engine information
management systems or search engines. In certain instances, search
engines may enable a user to search the Web by inputting one or
more search terms or queries so as to try to locate or retrieve
information that may be relevant or useful to such a user.
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] Non-limiting and non-exhaustive aspects are described with
reference to the following figures, wherein like reference numerals
refer to like parts throughout the various figures unless otherwise
specified.
[0006] FIG. 1 is a schematic diagram illustrating an implementation
of an example computing environment.
[0007] FIG. 2 is a schematic diagram illustrating a summary of an
example process for on-line social information searches.
[0008] FIG. 3 is a schematic diagram illustrating an implementation
of a computing environment associated with one or more special
purpose computing apparatuses.
DETAILED DESCRIPTION
[0009] In the following detailed description, numerous specific
details are set forth to provide a thorough understanding of
claimed subject matter. However, it will be understood by those
skilled in the art that claimed subject matter may be practiced
without these specific details. In other instances, methods,
apparatuses, articles, systems, etc. that would be known by one of
ordinary skill have not been described in detail so as not to
obscure claimed subject matter.
[0010] Some example methods, apparatuses, or articles of
manufacture are disclosed herein that may be implemented,
partially, dominantly, or substantially, to facilitate or support
one or more processes or operations in connection with performing
information searches, such as, for example, on-line searches using
social survey-type queries. Typically, although not necessarily,
"on-line" may refer to a type of a process, operation, technique,
etc. of electronic communications that may be implemented or
otherwise supported, at least in part, using one or more
communications networks, such as, for example, the Internet, one or
more intranets, one or more communication device networks, or the
like. Communications networks may comprise, for example, any
suitable or desired wireless network, wired network, or any
combination thereof. In the context of on-line information
searches, a social search may refer to information searching in
which relevance of search results may, for example, be determined,
at least in part, by taking into account or considering social
content associated with one or more social networks, networking
parties, etc. or one or more social features or attributes
associated with one or more social networks, networking parties,
etc. Here, for example, a networking party, such as one or more
users, members, etc. associated with one or more social networks,
may create, originate, etc. social content in the form of status
updates, rating or review posts, news feeds, tweets, or the like
and may post or communicate social content within one or more
applicable social networks. As will be seen, one or more social
features or attributes of these users, members, etc., such as
demographics, political views, religious beliefs, locations, or the
like may be utilized, at least in part, to account for relevance,
filtering, etc. of social content in connection with on-line
information searches.
[0011] As used herein, the terms "social survey-type query,"
"social survey query," or simply "query" may be used
interchangeably and may refer to one or more search terms a user,
member, or client may specify or employ with a search engine to
retrieve social information accounting for one or more social
aspects or features of one or more members of a social network of a
user initiating or specifying the query. For example, a search
engine user may specify or input a query via a use case so as to
retrieve on-line information that may typically, although not
necessarily, be personalized or opinion-based, such as ratings,
reviews, news feeds, etc. having social relevance to such a user,
as described below. Use cases may generally refer to a form of user
scenarios related to a particular goal that may be formulated in
terms of a task specifying details with respect to such a goal
within a particular environment. By way of example, a use case may
be formulated into a query by entering or inputting a phrase "What
local deals have been liked by my friends in my city in the last
day?" into a search engine via an interface, though claimed subject
matter is not so limited. Certain aspects of formulated use cases
will be described in greater detail below. As will be seen, social
survey queries may, for example, be advantageously utilized to
retrieve or otherwise obtain socially relevant information in the
form of personalized or tailored social survey results or
interactive responses from one or more members of a social network
or a user issuing a query. As such, by accounting for or
considering a specific or particular connection (e.g., dialog-type,
etc.) between a user issuing a query and a user's social network,
human intelligence or input may be leveraged with a social
component resulting in locating, retrieving, providing, etc.
information, which otherwise may not be available via a traditional
on-line information search.
[0012] Generally, in this context, "social graph" or "social
network" may be used interchangeably and may refer to a social
grouping or arrangement established or existing via a
communications network, for example, such as a web-based network or
virtual community of social relationships communicating or sharing
information by posting social content via a suitable communications
network. In some cases, a social network may be represented via a
pattern of relationships in the form of associational ties or links
between interconnected nodes (e.g., users, members, etc.). Social
relationships between users, members, etc. of a social network may,
for example, be based, at least in part, on various types of
interdependency, such as friendship, kinship, common interests,
activities, events, relationships of workplace, geographic
location, religious beliefs, etc., though claimed subject matter is
not so limited.
[0013] A social network may comprise, for example, a public social
network, a private social network, or any combination thereof. For
example, a public social network may generally refer to a social
network in which social content (e.g., status updates, contacts,
posts, messages, etc.) may be visible to or shared among users,
members, etc. of the network or may otherwise be publicly
accessible. A private social network may, for example, refer to a
social network in which social content may be visible to or shared
among only certain users, members, etc. (e.g., close friends,
family, etc.) of the network or as permitted by these users,
members, etc., or social networking service. As will be seen, at
times, a social network may comprise, for example, one or more
sub-networks or sub-graphs, which may also be private, public, or
comprise any combination thereof. As a way of illustration, social
networks may include Facebook, MySpace, Linkedln, Yelp, XING,
Twitter, Jaiku, Tumblr, Plurk, Beeing, just to name a few examples.
Of course, such details relating to social networks are merely
examples, and claimed subject matter is not so limited. It should
be noted that example methods, apparatuses, or articles of
manufacture disclosed herein may be implemented in connection with
or otherwise supported by any social network, such as, for example,
one or more social networks mentioned above, as well as those not
listed or to be developed in the future.
[0014] Following the above discussion, as a way of illustration,
some examples of various use cases formulated into social survey
queries that may be used for on-line information searches may
include those shown in Table 1 below. As seen, on-line social
searches in connection with queries 1 through 6 may be tailored to
or directed towards particular social content, such as, for
example, one or more domain-specific private sub-graphs. As the
term used herein, "domain-specific" may refer a particular
grouping, aspect, field, set, property, concept, level, etc.
associated with a social network of a user issuing a query, such
as, for example, a particular sub-graph. Here, for example, a user
may tailor or direct a query towards a particular grouping or
sub-graph, such as "my Facebook friends" in Query 1, "my Indian
friends" in Query 2, "my democrat friends" in Query 3, "my friends
in Florida" in Query 5, etc. As also illustrated, optionally or
alternatively, social searches may be performed with respect to
public content using, for example, social survey queries tailored
to or directed towards one or more specific domains, such as the
public domain of "everyone living in London" (e.g., in Query 7), of
"spas in my city" (e.g., in Query 8), or of "men older than 30 in
Boston" (e.g., in Query 9). Of course, social survey queries
illustrated in Table 1 are merely examples, and claimed subject
matter is not limited in this regard.
TABLE-US-00001 TABLE 1 Example social survey queries. 1. "What did
my Facebook friends think of Prince of Persia, the movie" 2. "What
is an Indian restaurant in Sunnyvale, CA, that my Indian friends
check into/liked in the last 6 months" 3. "What did my democrat
friends think of Obama's healthcare reform bill" 4. "What
smartphone do most of my friends comment positively about" 5. "What
do my friends in Florida think of the oil spill in the Gulf" 6.
"What local deals have been liked by my friends in my city in the
last day" 7. "What are all the updates by everyone living in London
in the last 6 hours" 8. "What are all the deals posted by spas in
my city on Twitter this past weekend" 9. "What are all Irish bar
reviews by men older than 30 in Boston"
[0015] As was indicated, effectively or efficiently identifying or
locating social content on the Web may facilitate or support
information-seeking behavior of users, members, etc., for example,
leading to an increased usability of a search engine. As such, due
to, at least in part, the popularity of social networking, a search
engine may, for example, wish to include social content in a
listing of returned search results. Typically, although not
necessarily, social content may include ratings, reviews, news
feeds, comments, posts, or the like, some or most of which may have
a special, personal or otherwise applicable relevance to a user
issuing a query, the concept, which may be referred to, at least in
part, as social relevance. As used herein, the term "social
relevance" is to be interpreted broadly and may refer to a measure
of how pertinent particular social content (e.g., located,
retrieved, ranked, etc.) is to a specific user, member, etc., such
as, for example, a user issuing a query, a specific member(s) of a
particular social network, etc. As will be seen, in certain
implementations, social relevance may be represented, for example,
as a quantitative or qualitative evaluation of social content
(e.g., a social relevance or ranking score, etc.) that may be
based, at least in part, on one or more social aspects or features
of member(s) of a social network and a relation of such one or more
aspects or features of such member(s) to a social survey query or a
user issuing such a query. For example, social relevance may
account for or otherwise consider one or more social aspects or
features associated with a user issuing a query, such as a measure
of user social authority across the user's social network, traits
or similarities of a user to the user's on-line "social circle," or
other user-related information that may be available or known about
the user. To illustrate, a measure of user social authority across
the user's social network may be based, at least in part, on a
number of social friends, followers, etc. that the user has within
the user's network, as one possible example. Certain contextual or
temporal information based, at least in part, on keyword relevance,
for example, as well as recency of social content (e.g., postings
chronology, etc.) with respect to a user issuing a query as well as
the query itself, respectively, may also be considered. In certain
situations, social user-related information may be extracted or
acquired, for example, from a user's social profile associated with
the user's network account, as will also be seen. Of course, such
details are intended as merely examples, and claimed subject matter
is not so limited.
[0016] As was indicated, social communication arrangements
supported by the Internet, such as, for example, on-line social
networks, web-based virtual communities, etc. continue to evolve.
On-line social content in the form of, for example, news feeds,
blogs, portals, status updates, rating or review posts, tweets, or
the like may be shared by community members across one or more
on-line social networks and, at times, openly published on the Web.
Social networking is gradually becoming more widespread due to, at
least in part, its convenience, immediacy, portability, appeal,
etc., for example, thus, increasing a utility of information posted
or transmitted by on-line social networking community. As such, a
search engine may wish to include on-line social content in a
listing of search results returned in response to a query. However,
how to locate, retrieve, or rank on-line information in terms of
social relevance to a user, for example, continues to be an area of
development.
[0017] Today, a number of search engines are capable of returning
social content indexed, cached, or otherwise gathered, for example,
by real-time or near real-time streaming in, sampling, crawling, or
otherwise monitoring one or more sources of social information
(e.g., via subscription feeds, streaming information feeds, etc.)
across one or more social networks. As used herein, "real time" may
refer to amount of timeliness of content or information, which has
been delayed by an amount of time attributable to electronic
communication as well as other information processing. Typically,
although not necessarily, search engines may return socially
relevant content by identifying, for example, popular or
news-worthy contextual attributes of a particular query and feeding
or funneling such attributes to or otherwise searching a public
stream of popular or news-worthy social content as it becomes
available (e.g., published on the Web, posted on a social network,
etc.). As such, social search engines typically, although not
necessarily, may integrate popular or news-worthy social content
into keyword-related social searches using, for example,
information streams in the form of public updates from social
networking sites, such as Twitter, MySpace, Facebook, or the like.
Thus, in certain instances, a search may remain agnostic with
respect to where information is being streamed from, for example,
and may focus mainly on objectives of presenting a suitable or
desired combination of real-time, relevant, or context-aware social
information. In addition, at times, social search engines may be
overwhelmed with real-time or live information streams from a
number of information sources, which may affect or impair an
ability to filter or recognize and, thus, suitably rank socially
relevant content. For example, search engines overwhelmed with a
live stream of social content may be more prone to content
misclassifications resulting in locating, retrieving, ranking, etc.
irrelevant, less relevant, or otherwise unwanted social content,
such as spam, self-promotion, etc. Accordingly, it may be desirable
to develop one or more methods, systems, or apparatuses that may
account for or otherwise consider social content that may have a
special, personal, or otherwise applicable relevance to a
particular user, member, etc. so as to improve or otherwise
positively affect ranking, filtering, etc. in the context of
on-line information searches.
[0018] As will be described in greater detail below, a social
survey query may be formulated or otherwise specified by a user,
member, or client associated with one or more on-line social
networks, for example, and may be electronically processed in some
manner using suitable or desired techniques, such as
pattern-matching, language-modeling, or the like so as to arrive at
or generate a number of component parts or query entities. As used
herein, "entity" may refer to one or more lexical objects, such as
words, sentences, phrases, etc. descriptive of or otherwise
associated with one or more electronic documents representing
on-line social content that may be matched (e.g., mapped, etc.) or
otherwise semantically correspond to one or more query terms or
keywords based, at least in part, on one or more suitable query
matching techniques. Although claimed subject matter is not limited
in this regard, entities may comprise, for example, particular
restaurants, local deals, locations, user or member actions, etc.,
which may correspond to one or more facets occurring or
co-occurring with entities within the vocabulary of one or more
on-line social information sources, as will be seen. A vocabulary
may comprise, at least in part, a number of lexical objects
associated with a particular information source, such as one or
more news feeds, articles, status updates, databases, or like
collection of social information, just to name a few examples.
[0019] "Facet" may refer to one or more lexical objects
representative of one or more concepts, aspects, properties,
attributes, or characteristics of an entity. In some cases, a
facets may be defined, for example, via a directed relationship
between an entity e and a facet f, such as, for example, in a
faceted relationship or relation (e, f). A plurality of facets may
be related to a particular entity via a number of faceted
relations, such as, for example, subordinate, subsumed,
associational, dependent, curative, hierarchical, etc. By way of
example, the location entity "London" may be related to a large
number of facets, such as "Big Ben," "London Eye," "Tower Bridge,"
"British Museum," "Trafalgar Square," etc. through a subsumed
"city--landmarks" relation (e.g., London--Big Ben, London--Tower
Bridge, etc.). In addition to subsumed relations, an entity may
also have a number of associational or suggestive relations with
facets. As a way of illustration, the entity "Venice" may be
associated, for example, with or suggestively related to a number
of facets, such as "museums," "hotels," "wine tasting," "carnival,"
"sightseeing," gondolas," "graffiti," "film festival," etc. via a
"location--event/activity" relation. Of course, these are merely
examples, and claimed subject matter is not so limited.
[0020] Thus, in one particular implementation, a social survey
query may be processed in some manner and may be applied to or
executed across one or more on-line social networks or any part of
on-line social networks (e.g., sub-graphs, etc.), for example, to
perform a faceted or facet-like social search. Here, a faceted or
facet-like social search may comprise, for example, an information
search in which one or more facets (e.g., keyword-based restaurant
names, etc.) may be identified or captured in an applicable
domain-specific (e.g., Irish bars in Boston, etc.) on-line social
content (e.g., user or member reviews, ratings, opinions, comments,
etc.). Of course, these details relating to faceted or facet-like
searches are merely examples, and claimed subject matter is not
limited in this regard. Faceted or facet-like searches are known
and need not be described here in greater detail.
[0021] Accordingly, following the above discussion, domain-specific
social content (e.g., rating or review postings, comments, status
updates, etc.) as well as user or member-related attributes or
features (e.g., demographics, interests, locations, etc.)
associated with applicable on-line social networks, for example,
may be located and advantageously employed in connection with one
or more social components of a query represented by one or more
entities. For example, in an implementation, based, at least in
part, on particularities of social context of a query or so-called
query "socialness," a faceted search may be performed, at least in
part, by routing or directing towards or otherwise applying social
components of such a query across one or more domain-specific
sources of social information. As previously mentioned, a social
survey query may be routed or directed towards a specific domain,
such as the private social sub-graph of "my friends in Florida" or
"my immediate family," for example, thus, sufficiently
personalizing or tailoring search results to a particular user,
member, etc. so as to positively affect or improve social
relevance, ranking, filtering, or the like. Again, these details
are merely examples to which claimed subject matter is not
limited.
[0022] As will be seen, certain social aspects or features of a
user issuing a query as well as user-related content associated
with a particular social network may be taken into account or
otherwise considered. Social aspects or user-related content may be
utilized, for example, by an indexer or like process or function to
establish or maintain a social index or like collection of
information (e.g., a cache, etc.) accessible by a ranking function,
just to illustrate one possible implementation. Certain social
information associated with an index or cache may be used, for
example, by a ranking function to compute social relevance or
ranking scores determining a particular order of search results
based, at least in part, on one or more aspects or features
reflecting social relevance of a query to a user, member, etc. For
example, social ranking may be based, at least in part, on explicit
social relevance to a user issuing a query, implicit social
relevance to such a user, or any combination thereof. Typically,
although not necessarily, explicit social relevance may be
determined, at least in part, from a query itself (e.g., via
keywords, entities, etc.), and implicit social relevance may be
determined, at least in part, from user-related information not
explicitly specified by a query. As a way of illustration, explicit
social relevance may comprise, for example, a user-specified
domain, sub-graph, gender, age, etc. Implicit social relevance may
comprise, for example, a current location of a user determined via
a media access control (MAC) address by a location-aware smart
phone of the user, by way of another illustration. Results of
ranking may be implemented, partially, dominantly, or
substantially, for use with a search engine or other information
management systems, for example, responsive to search queries,
social survey-type or otherwise, though claimed subject matter is
not so limited.
[0023] Before describing some example methods, apparatuses, or
articles of manufacture in greater detail, sections below will
first introduce certain aspects of an example computing environment
in which information searches, social or otherwise, may be
performed. It should be appreciated, however, that techniques
provided herein as well as claimed subject matter are not limited
to this example implementation. For example, techniques provided
herein may be used in a variety of information processing
environments, such as social database applications, language
processing or modeling applications, or the like, such as may be
implemented by a special purpose computing device, though claimed
subject matter is not so limited. In addition, any implementations,
embodiments, or configurations described herein as "example" are
described primarily for purposes of illustration and are not to be
construed as preferred or desired over other implementations,
embodiments, or configurations.
[0024] The Internet comprises a worldwide system of computer
networks and is a public, self-sustaining facility that is
accessible to tens of millions of people worldwide. Currently, the
most widely used part of the Internet appears to be the World Wide
Web, or simply the Web, which may be considered an Internet service
organizing information via use of hypermedia (e.g., embedded
references, hyperlinks, etc.). Considering the large amount of
resources available on the Web, it may be desirable to employ a
search engine to help locate or retrieve relevant or useful
information, such as, for example, one or more documents of a
particular subject or interest. A "document," "web document," or
"electronic document, as the terms used herein, are to be
interpreted broadly and may include one or more stored signals
representing any source code, text, image, audio, video file, or
like information that may be read or processed in some manner by a
special purpose computing platform and may be played or displayed
to or by a user, member, or client. Documents may include one or
more embedded references or hyperlinks to images, audio or video
files, or other documents. For example, one type of reference that
may be embedded in a document and used to identify or locate other
documents may comprise a Uniform Resource Locator (URL). As a way
of illustration, documents may include a news feed, a rating or
review post, a status update, a portal, a blog post, a tweet, an
e-mail, a text message, an Extensible Markup Language (XML)
document, a web page, a media file, a page pointed to by a URL,
just to name a few examples.
[0025] In the context of information searches, social or otherwise,
a query may be submitted via an interface, such as a graphical user
interface (GUI), for example, by entering certain words or phrases
to be queried, and a search engine may return a search results
page, which may include a number of documents typically, although
not necessarily, listed in a particular order. Under some
circumstances, it may also be desirable for a search engine to
utilize one or more techniques or processes to rank documents so as
to assist in presenting relevant or useful search results in an
efficient or effective manner. Accordingly, a search engine may
employ one or more functions or operations to rank documents
estimated to be relevant or useful (e.g., more recent, etc.) based,
at least in part, on relevance scores, ranking scores, or some
other measure such that more relevant or useful documents may be
presented or displayed more prominently among a listing of search
results (e.g., more likely to be seen by a user, member, etc.).
Typically, although not necessarily, for a given query, a ranking
function may determine or calculate a relevance score, ranking
score, etc. for one or more documents by measuring or estimating
relevance of one or more documents to a query. In the context of a
social search, a ranking function may also account for or otherwise
consider certain social aspects or features of a user issuing a
query, for example, as well as public or private content associated
with a particular domain, as previously mentioned.
[0026] As used herein, a "relevance score" or "ranking score" may
refer to a quantitative or qualitative evaluation of a document
based, at least in part, on one or more aspects or features (e.g.,
social, etc.) of that document with respect to a user issuing a
query as well as a relation of these aspects or features to a query
(e.g., keyword relevance, recency, etc.). A relevance or ranking
score may comprise, for example, one or more signal sample values
(e.g., on a pre-defined scale) calculated electronically or
otherwise assigned to a document and may be used, partially,
dominantly, or substantially, to rank documents with respect to a
query, social survey-type or otherwise. It should be noted,
however, that these are merely illustrative examples relating to
relevance or ranking scores, and that claimed subject matter is not
so limited. Following the above discussion, in processing a query,
a search engine may place documents that are deemed to be more
likely to be relevant or useful (e.g., with higher relevance
scores, ranking scores, etc.) in a higher position or slot on a
returned search results page, and documents that are deemed to be
less likely to be relevant or useful (e.g., with lower relevance
scores, ranking scores, etc.) may be placed in lower positions or
slots among search results, for example. A user, member, etc.,
thus, may receive and view a web page or other electronic document
that may include a listing of search results presented, for
example, in decreasing order of social relevance, just to
illustrate one possible implementation. As will also be seen,
search results may reflect, in whole or in part, a recency or
freshness of a document, for example, meaning that documents may be
ranked based, at least in part, on an order in which documents are
published or posted (e.g., on the Web, social networking web site,
rating or review portal, etc.).
[0027] With a large amount of information being added to the Web
daily, particularly social networking information, for example,
maintaining an up-to-date index via a crawl may be a challenging or
computationally expensive task. Typically, although not
necessarily, a crawler may perform a new crawl or update an index
of documents periodically. Constraints, such as size of the Web,
cost or finite nature of bandwidth for conducting crawls,
especially of deep Web resources, for example, may contribute to
slower network scan rates. Accordingly, in an implementation, one
or more real-time or near real-time indexing or caching techniques
may be utilized, for example, to return socially relevant or useful
information in response to a query. As a way of illustration,
certain search engines may facilitate or support quicker
indexation, for example, by streaming in or monitoring on-line
content at, upon, or soon after its posting or publication (e.g.,
via streaming or subscription feeds, application programming
interface (API) updates, etc.) such that social content may be
found while it may still be considered relevant or useful. Of
course, these are merely details relating to real-time or near
real-time indexing or caching techniques, and claimed subject
matter is not limited in this regard.
[0028] Attention is now drawn to FIG. 1, which is a schematic
diagram illustrating certain features of an implementation of an
example computing environment 100 capable of facilitating or
supporting, in whole or in part, one or more processes or
operations in connection with performing information searches, such
as, for example, on-line searches using social survey-type queries.
Example computing environment 100 may be operatively enabled using
one or more special purpose computing apparatuses, information
communication devices, information storage devices,
computer-readable media, applications or instructions, various
electrical or electronic circuitry and components, input signal
information, etc., as described herein with reference to particular
example implementations.
[0029] As illustrated in the present example, computing environment
100 may include one or more special purpose computing platforms,
such as, for example, an Information Integration System (IIS) 102
that may be operatively coupled to a communications network 104
that a user, member, or client may employ in order to communicate
with IIS 102 by utilizing resources 106. Resources 106 may
comprise, for example, one or more special purpose computing
devices or platforms. It should be appreciated that IIS 102 may be
implemented in the context of one or more information management
systems associated with public networks (e.g., the Internet, the
World Wide Web) private networks (e.g., intranets), public or
private search engines, Real Simple Syndication (RSS) or Atom
Syndication (Atom)-based applications, etc., just to name a few
examples.
[0030] Resources 106 may comprise a desktop computer, mobile
device, personal digital assistant, etc., for example, capable of
communicating with or otherwise having access to the Internet via a
wired or wireless communications network. Resources 106 may include
a browser 108 and a user interface 110, such as a graphical user
interface (GUI), for example, that may initiate transmission of one
or more electrical digital signals representing a query. Browser
108 may facilitate access to or viewing of documents via the
Internet, for example, such as HTML web pages, pages formatted for
mobile devices (e.g., WML, XHTML Mobile Profile, WAP 2.0, C-HTML,
etc.), or the like. User interface 110 may interoperate with any
suitable input device (e.g., keyboard, mouse, touch screen,
digitizing stylus, etc.) or output device (e.g., display, speakers,
etc.) for interaction with resources 106. It should be noted that
even though a certain number of resources 106 are illustrated in
FIG. 1, it should be appreciated that any number of resources may
be operatively coupled to IIS 102 via, for example, any suitable
communications network, such as communications network 104, for
example.
[0031] In one particular implementation, IIS 102 may include one or
more digital signal information indexing or crawling mechanisms,
represented generally by an indexer 112, capable of accessing
network resources 114. Indexer 112 may store all or part of located
documents (e.g., URLs, etc.) in a database 116, for example. IIS
102 may further include a search engine 124 supported by a suitable
index or cache represented herein, for example, by a social index
126, just to illustrate one possible implementation. Search engine
124 may be operatively enabled to search for information associated
with network resources 114. For example, search engine 124 may
communicate with user interface 110 and may retrieve for display
via resources 106 a listing of socially relevant search results
associated with social index 126 in response to one or more digital
signals representing a social survey query, though claimed subject
matter is not so limited.
[0032] Network resources 114 may include any organized collection
of any type of information, for example, represented by binary
digital signals accessible over the Internet or associated with an
intranet (e.g., documents, web sites, databases, discussion forums,
ration or review posts, etc.). As was indicated, in certain
implementations, network resources 114 may include private or
public social content (e.g., social networks, graphs, sub-graphs,
etc.) as well as one or more user or member-related social features
or attributes. It should be noted that, optionally or
alternatively, one or more user or member-related features or
attributes (e.g., demographic information, MAC addresses or session
locations, etc.) may be stored within IIS 102, for example, in the
form of binary digital signals in database 116 or social index 126,
though claimed subject matter is not so limited, of course.
[0033] In certain implementations, information associated with
social index 126 may be generated by an information extraction
engine 128 based, at least in part, on located or extracted content
associated, for example, with one or more information sources
(e.g., domain-specific social graphs, sub-graphs, etc.) during
indexing, caching, crawling, etc, just to illustrate one possible
implementation. As seen in this example, information extraction
engine 128 may further include or otherwise be operatively coupled
to a segmenter 130 capable of facilitating or supporting one or
more processes or operations in connection with query parsing,
segmentation, mapping, etc. using one or more suitable or desired
techniques (e.g., pattern-matching, language modeling, etc.). One
or more processes or operations in connection with query parsing,
segmentation, etc. will be described in greater detail below with
reference to Table 3.
[0034] As was indicated, it may be advantageous to utilize one or
more real-time indexing or caching techniques or processes, for
example, to keep social index 126 sufficiently updated with
socially relevant on-line content. To illustrate, IIS 102 may be
operatively enabled to subscribe, for example, to one or more
social networking platforms or services via a streaming information
feed, such as a live or direct feed, as indicated generally by
dashed line at 132. In one particular implementation, IIS 102 may
be enabled to subscribe to the Twitter streaming application
programming interface (API) or Twitter "firehose" feed, for
example, thus, having social content streamed in real time or near
real time so as to facilitate or support more effective or
efficient searching, indexing, caching, archiving, etc., for
example. As will be described in greater detail below, in certain
implementations, on-line social content (e.g., searched, indexed,
cached, archived, etc.), for example, from two or more information
sources may be joined in some manner so as to enhance social
relevance of search results. For example, IIS 102 may be enabled to
recognize that two (or more) ratings or reviews with respect to the
same entity (e.g., a specific restaurant, etc.) that were streamed
in, indexed, cached, or otherwise acquired from two (or more)
different social networking web sites (e.g., Twitter and Facebook,
etc.) actually came from the same user, member, etc. and, as such,
may be advantageously utilized in connection with a domain-specific
search across multiple social networks. In this illustrated
example, such ratings or reviews may be joined together based, at
least in part, on a common identifier (e.g., name, e-mail address,
physical location, etc.) with respect to such a user, member, etc.
In addition, social information may be joined, for example, in
instances where a query may be sufficiently general in nature so as
to apply across multiple social networks, sub-graphs, etc., thus,
enhancing social relevance of search results (e.g., accounting for
or considering more reviews, ratings, feedbacks, opinions, surveys,
etc.). Of course, these are merely examples to which claimed
subject matter is not limited.
[0035] As previously mentioned, it may be desirable for a search
engine to employ one or more operations or processes to rank search
results so as to assist in presenting relevant or useful
information in response to a query. Accordingly, IIS 102 may employ
one or more ranking functions, indicated generally by dashed lines
at 132, to rank search results in an order that may, for example,
be based, at least in part, on a social relevance, posting or
publishing chronology, etc, just to illustrate a few possible
implementations. For example, in one particular implementation,
ranking function(s) 132 may determine a particular order of ranking
based, at least in part, on one or more social aspects or features
associated with a user issuing a query, such as a user's centrality
or social authority across one or more social networks, sub-graphs,
etc. (e.g., how many social friends, followers, etc. a user has,
etc.). In another possible implementation, ranking function(s) 132
may order search results based, at least in part, on keyword
relevance or, optionally or alternatively, on similarities of a
user, member, etc. to the user's "social circle" (e.g., friends,
co-workers, etc.), such as age, gender, or the like. Also, in
certain implementations, ranking may be based, at least in part, on
chronological ordering of located search results, such as, for
example, freshness or recency of on-line posting or publishing, as
previously mentioned. Certain aspects with respect to ranking of
social information in connection with domain-specific on-line
searches will be described in greater detail below with reference
to FIG. 2. In one particular implementation, ranking function(s)
132 may be capable of aggregating sample relevance values (e.g.,
points or star-based ratings, reviews, etc.) in some manner so as
to arrive at a relevance or ranking score for a document using one
or more suitable or desired aggregation techniques (e.g.,
averaging, etc.), as will also be seen. Of course, such details are
merely examples, and claimed subject matter is not limited in this
regard. It should be noted that ranking function(s) 132 may be
included in search engine 124 or, optionally or alternatively, may
be operatively coupled to it. As illustrated, IIS 102 may further
include a processor 134 that may be operatively enabled to execute
special purpose computer-readable code or instructions or to
implement suitable or desired operations or processes associated
with example environment 100, for example.
[0036] In operative use, a user, member, or client may access a
particular search engine website (e.g., www.yahoo.com,
http://search.twitter.com, http://www.yelp.com,
http://tweetmeme.com/search, etc.), for example, and may submit or
specify a query (e.g., type into a search engine interface, etc.)
by utilizing resources 106. In one particular implementation, a
query may be specified or formulated by selecting a suitable or
desired use case to be queried (e.g., "What did my Facebook friends
think of this movie?", etc.) from a drop-down menu, for example,
resulting from performing a "mouse-over" or hover-box operation
(e.g., with a cursor, arrow, etc.) over a corresponding movie title
on a social networking web site. Of course, this is merely one
possible example relating to specifying or formulating a use case
into a query, and claimed subject matter is not so limited. For
example, in certain implementations, a use case may be specified or
formulated into a query by highlighting or selecting a suitable or
desired use case (e.g., "Which new dinner entrees have been
recommended by my Indian friends in the last month?", etc.) from
partially transparent options (e.g., a drop-down list, check boxes
or radio buttons, tab panel, etc.) overlaying a web page with a
particular subject of interest (e.g., a home page of a specific
restaurant, etc.), just to illustrate another non-limiting example.
Browser 108 may initiate communication of one or more electrical
digital signals representing a query from resources 106 to IIS 102
via communications network 104. IIS 102 may access or look up a
cache or social index 126 and establish a listing of documents
based, at least in part, on an order in accordance with ranking
function(s) 132, for example. IIS 102 may communicate a listing to
resources 106 for displaying, for example, via user interface
110.
[0037] With this in mind, example techniques will now be described
in greater detail that may be implemented, partially, dominantly,
or substantially, to facilitate or support one or more processes or
operations in connection with performing information searches, such
as, for example, domain-specific on-line searches using social
survey-type queries in an effective or efficient manner. As was
indicated, example techniques presented herein may be implemented
in connection with one or more social networking platforms or
applications capable of executing instructions represented by
digital signals. For example, in one particular implementation,
example techniques may utilize, in whole or in part, a
special-purpose software application residing on one or more canvas
pages associated with a suitable or desired networking platform
(e.g., Facebook, MySpace, etc.) but using social information
indexed, cached, archived, aggregated, etc. on one or more Yahoo!
servers or platforms, such as one or more Yahoo! Open Strategy
(YOS) platforms. Here, for example, a search engine user or a
member of a particular social network (e.g., Facebook, MySpace,
etc.) may input or specify a query with respect to a particular use
case (e.g., a social survey query, etc.) in a search engine
interface associated with a network, and the query may be routed,
directed towards, or applied in connection with a social content
indexed, cached, archived, aggregated, etc. from a number of
information sources (e.g., social networks, sub-graphs, etc.) on
one or more YOS platforms (e.g., Yahoo! Applications Platform
(YAP), Yahoo! Social Platform (YSP), etc.). As such, a particular
use case may result, for example, in multiple queries
advantageously applied across a number of social information
sources utilizing one or more Yahoo! servers or platforms. Search
results located or retrieved, for example, at YOS may be
subsequently returned or displayed to a user, member, etc. at or in
connection with a social network (e.g., Facebook, MySpace, etc.) of
a user issuing a query. Of course, such details are merely
examples, and claimed subject matter is not so limited.
[0038] In another implementation, example techniques may utilize,
in whole or in part, an application integrated with an on-line
search engine associated with a particular service provider, such
as a YAP application, for example, residing on a suitable
Yahoo!.RTM. platform (e.g., www.yahoo.com), though claimed subject
matter is not so limited, of course. Here, for example, such an
application may be built on top of YAP and may be utilized,
partially, dominantly, or substantially, as an enhancement to
currently available Updates Search YAP application, just to
illustrate one possible implementation. Optionally or
alternatively, domain-specific on-line social searches may be
implemented using, for example, an OpenSocial application developed
based, at least in part, on Yahoo! OpenSocial platform at YAP and,
as such, available for distribution across any suitable web site
(e.g., publisher web site, blogger web page or portal, etc.) that
may support one or more suitable or desired OpenSocial functions
(e.g., MySpace, etc.). In yet another implementation, example
techniques may comprise, at least in part, utilizing a web site or
web page (e.g., stand-alone, separate, etc.) that, in some
instances, may be associated with an on-line service provider. To
illustrate, a stand-alone or separate web page may comprise an
on-line property or portal page at Yahoo!, for example, wherein a
social search may be presented via one or more suitable or desired
search engine interfaces or toolbars (e.g., via
http://www.bing.com/social, etc.) featuring, for example, one or
more APIs that may integrate or connect various social networks
(e.g., Facebook, Yelp, etc.) into or with Yahoo! search
infrastructure. Of course, these are merely examples relating to
various possible implementations to which claimed subject matter is
not limited.
[0039] FIG. 2 is a schematic diagram illustrating a summary of an
example process 200 that may be implemented, partially, dominantly,
or substantially, to facilitate or support certain on-line
information searches, such as, for example, domain-specific on-line
searches using social survey-type queries. It should be noted that
information applied or produced, such as, for example, results
associated with example process 200 may be represented by one or
more digital signals. It should also be appreciated that even
though one or more operations are illustrated or described with
respect to a certain sequence, other sequences including, for
example, concurrent operations may also be employed. In addition,
although the description below references particular aspects or
features illustrated in certain other figures (e.g., FIG. 1, etc.),
one or more operations may be performed with other aspects or
features.
[0040] As seen, example process 200 may comprise, for example, a
service provider, as schematically referenced at 202, associated
with a suitable or desired IIS comprising a search engine, though
claimed subject matter is not so limited. As previously mentioned,
a search engine may be capable of obtaining socially relevant
on-line information in connection with networking parties (e.g.,
one or more users, members, etc.) of one or more on-line social
networks of a user issuing a query. For example, a social search
engine associated with service provider 202 may be capable of
indexing, caching, archiving, etc. on-line social content
associated with one or more sources of social information (e.g.,
social networks, sub-graphs, etc.) using suitable or desired
techniques so as to keep, for example, an index 204 or a cache 206
sufficiently updated. As seen in this illustrated example, service
provider 202 may be capable of subscribing to one or more social
networking platforms via a streaming information feed 208, such as
the Twitter "firehose," for example, wherein social information may
typically, although not necessarily, be indexed or archived for a
certain period of time (e.g., a several days, weeks, months, etc.),
depending, at least in part, on a subscription policy. Optionally
or alternatively, social information may be queried on-demand
using, for example, one or more suitable or desired stream, search,
or updates APIs, such as a real-time search API (e.g., Facebook
stream, Yahoo! Updates API, etc.), indicated generally at 210.
Here, for example, process 200 may employ one or more suitable or
desired caching techniques to facilitate or support access to
real-time social information in an effective or efficient manner,
as was indicated. In addition, in one particular implementation,
archiving of certain on-line social information may be restricted
or otherwise limited (e.g., due to restriction policies, contracts,
agreements, etc.), in which case service provider 202 may be
capable of or enabled to subscribe, for example, to certain updates
(e.g., selected, suitable, desired, etc.) and may be notified as
they occur (e.g., via MySpace publish/subscribe APIs, etc.). Of
course, such details relating to indexing, caching, archiving, etc.
of on-line social content are merely examples, and claimed subject
matter is not limited in this regard.
[0041] As previously mentioned, in an implementation, certain
on-line social content from two or more information sources, such
as, for example, two or more streaming information feeds (e.g.,
Twitter and Facebook, etc.) may be joined based, at least in part
on a common content identifier (e.g., user or member's name, e-mail
address, physical address, etc.). For example, an IIS associated
with service provider 202 may be capable of recognizing that a
particular user, member, etc. providing a comment, review, rating,
or the like in connection with a certain streaming information feed
(e.g., from Twitter, etc.) is the same user, member, etc. providing
a comment, review, rating, or the like in connection with another
information feed (e.g., from Facebook, etc.). Accordingly, such
on-line social content may be joined so as to account for or
otherwise consider socially relevant information across multiple
user-related domains (e.g., Twitter and Facebook social networks,
sub-graphs, etc.), for example, thus, enhancing social relevance of
search results. As was also indicated, on-line social information
from two or more sources may be joined, for example, in instances
where a query may be sufficiently general in nature so as to apply
across multiple social networks, sub-graphs, etc., thus,
advantageously increasing the size of a particular user-related
domain as well as its applicability. Having a larger domain may,
for example, enhance social relevance of search results by
accounting for or considering a larger number of users, members,
etc. and, thus, social surveys (e.g., reviews, ratings, opinions,
etc.) with respect to a particular use case (e.g., how many users,
members, etc. agree that a particular restaurant, hotel, bar, etc.
is good, better, best, etc.). Of course, claimed subject matter is
not limited in this regard.
[0042] In an implementation, on-line information reflecting, for
example, certain social aspects or features in connection with a
user, member, etc. associated with one or more social networks,
sub-graphs, etc. may be accessed, extracted or otherwise collected
in some manner so as to facilitate or support domain-specific
on-line social searches. In certain simulations or experiments, it
has been observed that a format in which user-related social
information is stored (e.g., on-line, in a user or member social
profile, network account, etc.) may prove to be less important than
availability of certain aspects or features with respect to a
particular user, member, etc., for example, so as to enable on-line
social searches for use cases, though claimed subject matter is not
limited to such an observation, of course. By way of example but
not limitation, one possible format suitable for facilitating or
supporting domain-specific on-line social searches may include one
represented in Table 2 below. Thus, consider:
TABLE-US-00002 TABLE 2 Example social information format. record: {
source: { name: <facebook, twitter, linkedin, buzz, yelp, imdb
etc.> } type: { name: status, comment, like, R&R, share,
bookmark, pic, vid } friend: { user id: user_id, location: woeid,
type: user_entity_type eg. democrat or hipster, gender: male or
female, age: number, length_of_contact: time in months eg. friends
since last year } entity/topic: { name: <politics, prince of
persia, movies, restaurants, hotels, concerts, music, britney
spears etc. } note: CAP entity ids may be substituted keyword: list
of tokens time: date or time eg. last six months or today or last
hour }
[0043] Here, for example, "record" may comprise any suitable or
desired information that may be searchable by or in connection with
a particular (e.g., current, etc.) user, member, etc. As seen,
"record" may include, for example, a number of sample field values
allowing for value matching based, at least in part, on a value
present or realized within a particular field. It should be noted
that in some instances certain field values may not be available,
may be ignored, or remain unmatched, though claimed subject matter
is not so limited. It should also be noted that one or more
negative matches may be detected meaning that records with certain
sample values may be selectively excluded (e.g., during a search,
etc.), as will be seen.
[0044] Following the above discussion, a user, member, etc. may
input, specify, formulate, etc. a particular use case into a query
(e.g., a social survey query, etc.) in a search engine interface,
for example, associated with a particular service provider using
any suitable or desired techniques, such as one or more techniques
described above. At operation 212, a query may be processed in some
manner using one or more suitable techniques, such as, for example,
one or more existing pattern-matching or language-modeling
techniques. As a way of illustration, string matching processes may
be used, in whole or in part, among a plurality of string matching
approaches to find occurrences of a pattern within another,
typically, although not necessarily, longer or larger pattern.
Examples of such processes may include Karp-Rabin, Boyer-Moore,
Knuth-Morris-Pratt, Real Time Matching process, etc., just to name
a few; although, of course, claimed subject matter is not limited
to these particular examples. It should be noted that a
normalization procedure may be implemented, in whole or in part, to
enhance, for example, same-value string recognition or to account
for particularities of various information sources.
[0045] As another illustration, a trigram-based language-modeling
technique may be utilized, for example, in connection with
processing a query, which may capture one or more aspects or
properties of a language (e.g., natural, artificial, constructed,
formal, symbolic, etc.) based, at least in part, on one or more
sample values, which may, partially, dominantly, or substantially,
be attributed to or otherwise associated with a language. For
example, in one particular implementation, one or more sample
values may comprise, in whole or in part, one or more keywords,
contextual terms, facet terms, etc. represented by one or more
tokens of text present or embedded in a specified or formulated
query. Language modeling techniques are known and need not be
described here in greater detail.
[0046] These or other like techniques, processes, or procedures may
be implemented, in whole or in part, to facilitate or otherwise
support a mapping of use cases to queries at operation 212.
Processes for query mapping may, for example, depend, at least in
part, on type of an entity (e.g., restaurant or movie, etc.) or
streaming information feed/API available. Thus, in one particular
implementation, a use case may be segmented and mapped to a query
via a suitable or desired parsing or segmentation-type process that
may be executed, for example, against a suitable or desired index
(e.g., social index 126 of FIG. 1, etc.), cache (e.g., cache 206 of
FIG. 2, etc.), or available API. By way of example but not
limitation, Table 3 shown below illustrates examples of query
segmentations that may be taken into consideration, in whole or in
part, so as to facilitate or support one or more processes or
operations associated, for example, with domain-specific on-line
social searches. It should be noted, however, that these are merely
illustrative examples, and that claimed subject matter is not
limited to particular examples shown. Techniques or processes
associated with query segmentations or mapping are known and need
not be described here with greater particularity.
TABLE-US-00003 TABLE 3 Examples of query segmentations. 1. "What is
an indian restaurant in Sunnyvale, CA that my indian friends check
into/like-d in the last 6 months" is segmented into a search for:
.cndot. entity type = indian restaurant, location = Sunnyvale, CA,
time = last 6 months, source = all friends (*), action = checkin 2.
"What local deals have been liked by my friends in my city in the
last day" .cndot. entity_type = local deals, location = <user's
current location>, time = last day, action = like
[0047] At operation 214, a specific or tailored plan with respect
to querying or executing a particular use case (e.g., specified,
formulated, etc.) represented by a social survey query, for
example, across one or more social networks may be electronically
generated. Here, for example, an execution may be planned based, at
least in part, on one or more available sources of social
information (e.g., indexed, cached, streamed in, etc.) that may be
represented, for example, via sample field values, such as one or
more "source" field values=<facebook, twitter, linkedin, buzz,
yelp, imdb etc.> of Table 2, just to illustrate one possible
implementation. It should be noted that in certain implementations
an execution may be planned with results restricted to a particular
time period or window (e.g., to querying a Facebook stream with a
"movie" query for the period of last three months, etc.), though
claimed subject matter is not so limited.
[0048] In an implementation, a plan may include, for example,
recognizing an inputted query as a social survey query based, at
least in part, on identifying certain patterns associated with or
representative of social survey-type queries (e.g., longer queries
with a social component, directed towards specific domains of
public or private social users, members, etc., phrased as a
survey-type question, etc.). Optionally or alternatively, a query
may be identified as a social survey query by determining where
such a query came from, meaning that if a particular query was
issued by a Facebook user (e.g., originated from a social network,
etc.) then an initial assumption may be made that such a query is
of a social type. In addition, one or more contextual terms, facet
terms, domain-identifying terms, or the like may be identified
based, at least in part, on one or more query entities obtained,
for example, as a result of query processing. For example, a
specific domain to which a particular query may apply to or may be
directed towards may be identified by recognizing associational
attributes of query entities representative of or corresponding to
a certain social graph (e.g., "my friends on Facebook," etc.), a
sub-section of a social graph or sub-graph (e.g., "my Indian
friends on Facebook," etc.), or the like. Optionally or
alternatively, one or more processes with respect to identifying
social survey-type queries or specific applicable domains may be
implemented or performed separately from operation 214, such as,
for example, in connection with operation 212, though claimed
subject matter is not so limited, of course.
[0049] With regard to operation 216, a process may execute
instructions on a special purpose computing apparatus to apply,
route, or otherwise direct a query towards a specific applicable
(e.g., user-related, etc.) domain, for example, taking into account
or considering particularities of social context or "socialness" of
such a query. For example, in an implementation, a number of fields
associated with a suitable or desired record, such as a record
illustrated in connection with Table 2, may be processed in some
manner so as to selectively include or exclude records with certain
field values (e.g., entity_type=restaurant and update_time in last
1 week, etc.), just to illustrate one possible implementation. It
should be noted that corresponding field values may be aggregated
in some manner using suitable aggregation techniques so as to
perform one or more computations to arrive, for example, at
suitable or desired statistical sample quantities, such as a single
rating for multiple star-based reviews (e.g., avg(rating) or
count(*), etc.), or the like. Some examples of statistical sample
quantities may include an average, a median, a mean, a percentile
of mean, a maximum, a sample number of instances or count, a ratio,
a rate, a frequency, etc., or any combination thereof. Of course,
these are merely examples, and claimed subject matter is not so
limited.
[0050] In an implementation, a process may further execute
instructions on a special purpose computing apparatus to rank, for
example, applicable records or results received in response to one
or more digital signals representing a query using one or more
suitable or desired ranking functions (e.g., machine-learned,
etc.). For example, a ranking function may compute a social
relevance or ranking score based, at least in part, on one or more
social aspects or features of a user, member, etc. of an applicable
social network, or other related information obtained from one or
more applicable records, as was indicated. More specifically, here,
for example, ranking may be based, at least in part, on social
relevance to a user issuing a query, meaning that search results
may be ordered based, at least in part, on how relevant applicable
record may be to such a user (e.g., ordered by user or friend
authority, keyword relevance, similarities of a "social circle of
friends" to a user issuing a query, etc.). As previously mentioned,
records or results may be ranked based, at least in part, on
explicit social relevance to a user issuing a query (e.g.,
user_gender=male, etc.), implicit social relevance to such a user
(e.g., user_device=smart phone, pc, etc.), or any combination
thereof. Optionally or alternatively, results may be ordered based,
at least in part, on recency of social content, such as postings
chronology, for example, as was also indicated. In addition, two
(or more) records that are equally recent may, for example, be
ranked by social relevance and vice-versa. Of course, these are
merely examples, and claimed subject matter is not limited in this
regard.
[0051] At operation 218, a process may further execute instructions
on a special purpose computing apparatus to serve or present a
listing of ranked search results to a user issuing a query. For
example, a process or system may transmit one or more digital
signals representing a listing of search results ranked, for
example, in accordance with social relevance or chronologically
(e.g., in real time, etc.) via an electronic communications network
to a user, member, etc. associated with one or more social networks
and may be displayed via a user interface, just to illustrate one
possible implementation.
[0052] Following the above discussion, some example technological
components, which may be taken into consideration, in whole or in
part, so as to facilitate or support one or more processes or
operations in connection with performing on-line social searches,
such as, for example, domain-specific on-line searches using social
survey-type queries may include those presented in Table 4 below.
It should be appreciated that Table 4, which is self-explanatory,
is provided herein by way of a non-limiting example, and that
claimed subject matter is not limited to particular technological
components shown.
TABLE-US-00004 TABLE 4 Example technological components. Resources
Component What it does (FTEs) Choices query parsing segments 1 FTE
qlas & segmentation query into entities query plan generates an
1/2 FTE qlas computation execution plan for segmented query data
store stores data in 1 FTE 1. apache flexible hbase schema 2.
cassandra format 3. vespa indexing indexed & 2 FTE 1. lucandra
searchable 2. vespa fields + ranking stream search queries real 1/2
FTE esper time stream
[0053] Here, full-time equivalent (FTE) may refer to an estimated
measure of involvement or contribution with respect to a particular
technological component and provided by way of example only so as
to illustrate one particular non-limiting approach. As seen in this
illustrated example, technological components may comprise, for
example, one or more suitable or desired database management
systems, information storage platforms, software, complex event
processing (CEP) components, or the like (e.g., Apache, Cassandra,
Esper, etc.) that may be used, in whole or in part, in conjunction
with one or more implementations described herein. It should be
noted that certain technological components, such as, for example,
components with respect to content or information storing may
depend on or be driven by, at least in part, applicable partnership
clauses (e.g., in subscription agreements, etc.). To illustrate,
Twitter social information may typically, although not necessarily,
be stored for months, and Facebook information may be stored for a
certain number of days. Optionally or alternatively, information
retention may be driven, at least in part, by entity type (e.g.,
store restaurant reviews for five months, hotel reviews for three
years, etc.). Of course, such details are merely examples, and
claimed subject matter is not limited in this regard. Also, those
of skill in the art may recognize that one or more components
illustrated in Table 4 or otherwise associated with performing
domain-specific on-line social searches, for example, may be
implemented in a variety of ways or may be rearranged, combined,
omitted, etc. without departing from illustrated principles.
[0054] FIG. 3 is a schematic diagram illustrating an example
computing environment 300 that may include one or more devices that
may be capable of implementing a process in connection with
performing on-line social searches, such as, for example,
domain-specific on-line searches using social survey-type queries.
Computing environment system 300 may include, for example, a first
device 302 and a second device 304, which may be operatively
coupled together via a network 306. In an embodiment, first device
302 and second device 304 may be representative of any electronic
device, appliance, or machine that may have capability to exchange
signal information over network 306. Network 306 may represent one
or more communication links, processes, or resources having
capability to support exchange or communication of signal
information between first device 302 and second device 304. Second
device 304 may include at least one processing unit 308 that may be
operatively coupled to a memory 310 through a bus 312. Processing
unit 308 may represent one or more circuits to perform at least a
portion of one or more signal information computing procedures or
processes.
[0055] Memory 310 may represent any signal storage mechanism. For
example, memory 310 may include a primary memory 314 and a
secondary memory 316. Primary memory 314 may include, for example,
a random access memory, read only memory, etc. in certain
implementations, secondary memory 316 may be operatively receptive
of, or otherwise have capability to be coupled to, a
computer-readable medium 318.
[0056] Computer-readable medium 318 may include, for example, any
medium that can store or provide access to signal information, such
as, for example, code or instructions for one or more devices in
operating environment 300. It should be understood that a storage
medium may typically, although not necessarily, be non-transitory
or may comprise a non-transitory device. In this context, a
non-transitory storage medium may include, for example, a device
that is physical or tangible, meaning that the device has a
concrete physical form, although the device may change state. For
example, one or more electrical binary digital signals
representative of information, in whole or in part, in the form of
zeros may change a state to represent information, in whole or in
part, as binary digital electrical signals in the form of ones, to
illustrate one possible implementation. As such, "non-transitory"
may refer, for example, to any medium or device remaining tangible
despite this change in state.
[0057] Second device 304 may include, for example, a communication
adapter or interface 320 that may provide for or otherwise support
communicative coupling of second device 304 to a network 306.
Second device 304 may include, for example, an input/output device
322. Input/output device 322 may represent one or more devices or
features that may be able to accept or otherwise input human or
machine instructions, or one or more devices or features that may
be able to deliver or otherwise output human or machine
instructions.
[0058] According to an implementation, one or more portions of an
apparatus, such as second device 304, for example, may store one or
more binary digital electronic signals representative of
information expressed as a particular state of a device such as,
for example, second device 304. For example, an electrical binary
digital signal representative of information may be "stored" in a
portion of memory 310 by affecting or changing a state of
particular memory locations, for example, to represent information
as binary digital electronic signals in the form of ones or zeros.
As such, in a particular implementation of an apparatus, such a
change of state of a portion of a memory within a device, such a
state of particular memory locations, for example, to store a
binary digital electronic signal representative of information
constitutes a transformation of a physical thing, for example,
memory device 310, to a different state or thing.
[0059] Thus, as illustrated in various example implementations or
techniques presented herein, in accordance with certain aspects, a
method may be provided for use as part of a special purpose
computing device or other like machine that accesses digital
signals from memory or processes digital signals to establish
transformed digital signals which may be stored in memory as part
of one or more information files or a database specifying or
otherwise associated with an index, social or otherwise.
[0060] Some portions of the detailed description herein are
presented in terms of algorithms or symbolic representations of
operations on binary digital signals stored within a memory of a
specific apparatus or special purpose computing device or platform.
In the context of this particular specification, the term specific
apparatus or the like includes a general purpose computer once it
is programmed to perform particular functions pursuant to
instructions from program software. Algorithmic descriptions or
symbolic representations are examples of techniques used by those
of ordinary skill in the signal processing or related arts to
convey the substance of their work to others skilled in the art. An
algorithm is here, and generally, is considered to be a
self-consistent sequence of operations or similar signal processing
leading to a desired result. In this context, operations or
processing involve physical manipulation of physical quantities.
Typically, although not necessarily, such quantities may take the
form of electrical or magnetic signals capable of being stored,
transferred, combined, compared or otherwise manipulated. It has
proven convenient at times, principally for reasons of common
usage, to refer to such signals as bits, data, values, elements,
symbols, characters, terms, numbers, numerals or the like. It
should be understood, however, that all of these or similar terms
are to be associated with appropriate physical quantities and are
merely convenient labels.
[0061] Unless specifically stated otherwise, as apparent from the
discussion herein, it is appreciated that throughout this
specification discussions utilizing terms such as "processing,"
"computing," "calculating," "determining" or the like refer to
actions or processes of a specific apparatus, such as a special
purpose computer or a similar special purpose electronic computing
device. In the context of this specification, therefore, a special
purpose computer or a similar special purpose electronic computing
device is capable of manipulating or transforming signals,
typically represented as physical electronic or magnetic quantities
within memories, registers, or other information storage devices,
transmission devices, or display devices of the special purpose
computer or similar special purpose electronic computing
device.
[0062] Terms, "and" and "or" as used herein, may include a variety
of meanings that also is expected to depend at least in part upon
the context in which such terms are used. Typically, "or" if used
to associate a list, such as A, B or C, is intended to mean A, B,
and C, here used in the inclusive sense, as well as A, B or C, here
used in the exclusive sense. In addition, the term "one or more" as
used herein may be used to describe any feature, structure, or
characteristic in the singular or may be used to describe some
combination of features, structures or characteristics. Though, it
should be noted that this is merely an illustrative example and
claimed subject matter is not limited to this example.
[0063] While certain example techniques have been described or
shown herein using various methods or systems, it should be
understood by those skilled in the art that various other
modifications may be made, or equivalents may be substituted,
without departing from claimed subject matter. Additionally, many
modifications may be made to adapt a particular situation to the
teachings of claimed subject matter without departing from the
central concept(s) described herein. Therefore, it is intended that
claimed subject matter not be limited to particular examples
disclosed, but that claimed subject matter may also include all
implementations falling within the scope of the appended claims, or
equivalents thereof.
* * * * *
References